tidyr use separate_rows over multiple columns

Question

I have a data.frame where some cells contain strings of comma separate values:

d <- data.frame(a=c(1:3), 
       b=c(\"name1, name2, name3\", \"name4\",          


        

Answer 1

You can use a pipe. Note that sep = ", " is automatically detected.

d %>% separate_rows(b) %>% separate_rows(c)
#   a     b      c
# 1 1 name1  name7
# 2 1 name2  name7
# 3 1 name3  name7
# 4 2 name4  name8
# 5 2 name4  name9
# 6 3 name5 name10
# 7 3 name6 name10

Note: Using tidyr version 0.6.0, where the %>% operator is included in the package.

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Update: Using @doscendodiscimus comment, we could use a for() loop and reassign d in each iteration. This way we can have as many columns as we like. We will use a character vector of column names, so we'll need to switch to the standard evaluation version, separate_rows_.

cols <- c("b", "c")
for(col in cols) {
    d <- separate_rows_(d, col)
}

which gives the updated d

  a     b      c
1 1 name1  name7
2 1 name2  name7
3 1 name3  name7
4 2 name4  name8
5 2 name4  name9
6 3 name5 name10
7 3 name6 name10

Answer 2

Here's an alternative approach using splitstackshape::cSplit and zoo::na.locf.

library(splitstackshape)
library(zoo)

df <- cSplit(d, 1:ncol(d), "long", sep = ",")
na.locf(df[rowSums(is.na(df)) != ncol(df),])
#    a     b      c
#1:  1 name1  name7
#2:  1 name2  name7
#3:  1 name3  name7
#4:  2 name4  name8
#5:  2 name4  name9
#6:  3 name5 name10
#7:  3 name6 name10